• 제목/요약/키워드: Initial value method

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AN ASYMPTOTIC INITIAL VALUE METHOD FOR SECOND ORDER SINGULAR PERTURBATION PROBLEMS OF CONVECTION-DIFFUSION TYPE WITH A DISCONTINUOUS SOURCE TERM

  • Valanarasu, T.;Ramanujam, N.
    • Journal of applied mathematics & informatics
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    • 제23권1_2호
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    • pp.141-152
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    • 2007
  • In this paper a numerical method is presented to solve singularly perturbed two points boundary value problems for second order ordinary differential equations consisting a discontinuous source term. First, in this method, an asymptotic expansion approximation of the solution of the boundary value problem is constructed using the basic ideas of a well known perturbation method WKB. Then some initial value problems and terminal value problems are constructed such that their solutions are the terms of this asymptotic expansion. These initial value problems are happened to be singularly perturbed problems and therefore fitted mesh method (Shishkin mesh) are used to solve these problems. Necessary error estimates are derived and examples provided to illustrate the method.

A WEIGHTED EULER METHOD FOR SOLVING STIFF INITIAL VALUE PROBLEMS

  • BEONG IN, YUN
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • 제26권4호
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    • pp.353-361
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    • 2022
  • For an initial value problem, using a weighted average between two adjacent approximates, we propose a simple one-step method based on the Euler method. This method is useful for solving stiff initial value problem, even when the step size is not very small. Moreover, it can be seen that the proposed method with some selected weights results in improved approximation errors.

AN IMPROVED IMPLICIT EULER METHOD FOR SOLVING INITIAL VALUE PROBLEMS

  • YUN, BEONG IN
    • Journal of the Korean Society for Industrial and Applied Mathematics
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    • 제26권3호
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    • pp.138-155
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    • 2022
  • To solve the initial value problem we present a new single-step implicit method based on the Euler method. We prove that the proposed method has convergence order 2. In practice, numerical results of the proposed method for some selected examples show an error tendency similar to the second-order Taylor method. It can also be found that this method is useful for stiff initial value problems, even when a small number of nodes are used. In addition, we extend the proposed method by using weighted averages with a parameter and show that its convergence order becomes 2 for the parameter near $\frac{1}{2}$. Moreover, it can be seen that the extended method with properly selected values of the parameter improves the approximation error more significantly.

LMS 알고리즘에서 최적 매개변수의 선택 폭 확대를 위한 초기치의 설정방법 (The Initial Value Setting-Up Method for Extending the Range of the Optimal Step Parameter under LMS Algorithm)

  • 조기량;안혁;추병윤;이춘재
    • 한국정보통신학회논문지
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    • 제7권2호
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    • pp.284-292
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    • 2003
  • 본 논문에서는 LMS 알고리즘을 이용하여 적응 시스템을 제어하는 경우, 최적 매개변수의 선택 폭을 늘리기 위한 초기치의 설정방법의 수치적 검토를 행했다. 초기치 설정은 대략의 값을 임의적으로 선택하는 일반적인 방법과 직접법에 의해 얻어진 근사적인 해를 초기치로서 가하는 방법을 이용하였으며, 이들을 최적지향성합성 문제에 적용하여 초기치가 매개변수의 선택 폭, 자승평균오차의 수렴속도, 그리고 수렴과정에서의 안정성 등에 미치는 영향을 비교하였다. 수치실험결과, 직접법을 이용한 초기치 선택방법은 일반적인 선택방법에 비해 매개변수의 선택 폭이 넓어짐은 물론 수렴성, 안정성 그리고 오차 개선 능력도 탁월함을 나타내었다.

AN INITIAL VALUE TECHNIQUE FOR SINGULARLY PERTURBED DIFFERENTIAL-DIFFERENCE EQUATIONS WITH A SMALL NEGATIVE SHIFT

  • Rao, R. Nageshwar;Chakravarthy, P. Pramod
    • Journal of applied mathematics & informatics
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    • 제31권1_2호
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    • pp.131-145
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    • 2013
  • In this paper, we present an initial value technique for solving singularly perturbed differential difference equations with a boundary layer at one end point. Taylor's series is used to tackle the terms containing shift provided the shift is of small order of singular perturbation parameter and obtained a singularly perturbed boundary value problem. This singularly perturbed boundary value problem is replaced by a pair of initial value problems. Classical fourth order Runge-Kutta method is used to solve these initial value problems. The effect of small shift on the boundary layer solution in both the cases, i.e., the boundary layer on the left side as well as the right side is discussed by considering numerical experiments. Several numerical examples are solved to demonstate the applicability of the method.

SOLVING SECOND ORDER SINGULARLY PERTURBED DELAY DIFFERENTIAL EQUATIONS WITH LAYER BEHAVIOR VIA INITIAL VALUE METHOD

  • GEBEYAW, WONDWOSEN;ANDARGIE, AWOKE;ADAMU, GETACHEW
    • Journal of applied mathematics & informatics
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    • 제36권3_4호
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    • pp.331-348
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    • 2018
  • In this paper, an initial value method for solving a class of singularly perturbed delay differential equations with layer behavior is proposed. In this approach, first the given problem is modified in to an equivalent singularly perturbed problem by approximating the term containing the delay using Taylor series expansion. Then from the modified problem, two explicit Initial Value Problems which are independent of the perturbation parameter, ${\varepsilon}$, are produced: the reduced problem and boundary layer correction problem. Finally, these problems are solved analytically and combined to give an approximate asymptotic solution to the original problem. To demonstrate the efficiency and applicability of the proposed method three linear and one nonlinear test problems are considered. The effect of the delay on the layer behavior of the solution is also examined. It is observed that for very small ${\varepsilon}$ the present method approximates the exact solution very well.

Comparison of parameter estimation methods for normal inverse Gaussian distribution

  • Yoon, Jeongyoen;Kim, Jiyeon;Song, Seongjoo
    • Communications for Statistical Applications and Methods
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    • 제27권1호
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    • pp.97-108
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    • 2020
  • This paper compares several methods for estimating parameters of normal inverse Gaussian distribution. Ordinary maximum likelihood estimation and the method of moment estimation often do not work properly due to restrictions on parameters. We examine the performance of adjusted estimation methods along with the ordinary maximum likelihood estimation and the method of moment estimation by simulation and real data application. We also see the effect of the initial value in estimation methods. The simulation results show that the ordinary maximum likelihood estimator is significantly affected by the initial value; in addition, the adjusted estimators have smaller root mean square error than ordinary estimators as well as less impact on the initial value. With real datasets, we obtain similar results to what we see in simulation studies. Based on the results of simulation and real data application, we suggest using adjusted maximum likelihood estimates with adjusted method of moment estimates as initial values to estimate the parameters of normal inverse Gaussian distribution.

고속 프랙탈 영상 부호화를 위한 개선한 초기 영상 추정법 (Improved Initial Image Estimation Method for a Fast Fractal Image Decoding)

  • 정태일;강경원;문광석
    • 수산해양기술연구
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    • 제33권1호
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    • pp.68-75
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    • 1997
  • In this paper, we propose the improved initial image estimation method for a fast fractal image decoding. When the correlation between a domain and a range is given as the linear equation, the value of initial image estimation using the conventional method is the intersection between its linear equation and y=x. If the gradient of linear equation is large, that the difference of the value between each adjacent pixels is large, the conventional method has disadvantage which has the impossibility of exact estimation. The method of the proposed initial image estimation performs well by two steps. he first step can improve the disadvantage of the conventional method. The second step upgrades the range value which was found previous step by referring information of its domain. Though the computational complexity for the initial image estimation increses slightly, the total computational complexity decreases by 30% than that of the conventional method because of diminishing in the number of iterations.

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A Study on The Optimization Method of The Initial Weights in Single Layer Perceptron

  • Cho, Yong-Jun;Lee, Yong-Goo
    • Journal of the Korean Data and Information Science Society
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    • 제15권2호
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    • pp.331-337
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    • 2004
  • In the analysis of massive volume data, a neural network model is a useful tool. To implement the Neural network model, it is important to select initial value. Since the initial values are generally used as random value in the neural network, the convergent performance and the prediction rate of model are not stable. To overcome the drawback a possible method use samples randomly selected from the whole data set. That is, coefficients estimated by logistic regression based on the samples are the initial values.

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An Error Embedded Runge-Kutta Method for Initial Value Problems

  • Bu, Sunyoung;Jung, WonKyu;Kim, Philsu
    • Kyungpook Mathematical Journal
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    • 제56권2호
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    • pp.311-327
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    • 2016
  • In this paper, we propose an error embedded Runge-Kutta method to improve the traditional embedded Runge-Kutta method. The proposed scheme can be applied into most explicit embedded Runge-Kutta methods. At each integration step, the proposed method is comprised of two equations for the solution and the error, respectively. These solution and error are obtained by solving an initial value problem whose solution has the information of the error at each integration step. The constructed algorithm controls both the error and the time step size simultaneously and possesses a good performance in the computational cost compared to the original method. For the assessment of the effectiveness, the van der Pol equation and another one having a difficulty for the global error control are numerically solved. Finally, a two-body Kepler problem is also used to assess the efficiency of the proposed algorithm.